Blood Pressure Abnormality data analysis

Dataset statistics

Number of variables	15
Number of observations	2000
Missing cells	1892
Missing cells (%)	6.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	234.5 KiB
Average record size in memory	120.1 B

Variable types

Numeric	8
Categorical	7

Warnings

`Blood_Pressure_Abnormality` is highly correlated with `Chronic_kidney_disease` and 1 other fields	High correlation
`Chronic_kidney_disease` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Adrenal_and_thyroid_disorders` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Blood_Pressure_Abnormality` is highly correlated with `Chronic_kidney_disease` and 1 other fields	High correlation
`Chronic_kidney_disease` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Adrenal_and_thyroid_disorders` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Blood_Pressure_Abnormality` is highly correlated with `Chronic_kidney_disease` and 1 other fields	High correlation
`Chronic_kidney_disease` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Adrenal_and_thyroid_disorders` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Blood_Pressure_Abnormality` is highly correlated with `Adrenal_and_thyroid_disorders` and 3 other fields	High correlation
`Adrenal_and_thyroid_disorders` is highly correlated with `Blood_Pressure_Abnormality` and 1 other fields	High correlation
`Genetic_Pedigree_Coefficient` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Chronic_kidney_disease` is highly correlated with `Blood_Pressure_Abnormality` and 1 other fields	High correlation
`Sex` is highly correlated with `Level_of_Hemoglobin`	High correlation
`Level_of_Hemoglobin` is highly correlated with `Blood_Pressure_Abnormality` and 1 other fields	High correlation
`Pregnancy` is highly correlated with `Sex`	High correlation
`Blood_Pressure_Abnormality` is highly correlated with `Adrenal_and_thyroid_disorders` and 1 other fields	High correlation
`Adrenal_and_thyroid_disorders` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Chronic_kidney_disease` is highly correlated with `Blood_Pressure_Abnormality`	High correlation
`Sex` is highly correlated with `Pregnancy`	High correlation
`Genetic_Pedigree_Coefficient` has 92 (4.6%) missing values	Missing
`Pregnancy` has 1558 (77.9%) missing values	Missing
`alcohol_consumption_per_day` has 242 (12.1%) missing values	Missing
`Patient_Number` is uniformly distributed	Uniform
`Patient_Number` has unique values	Unique

Reproduction

Analysis started	2021-08-08 17:53:19.940701
Analysis finished	2021-08-08 17:53:27.731653
Duration	7.79 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

Patient_Number
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	2000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1000.5

Minimum	1
Maximum	2000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	1
5-th percentile	100.95
Q1	500.75
median	1000.5
Q3	1500.25
95-th percentile	1900.05
Maximum	2000
Range	1999
Interquartile range (IQR)	999.5

Descriptive statistics

Standard deviation	577.4945887
Coefficient of variation (CV)	0.5772059857
Kurtosis	-1.2
Mean	1000.5
Median Absolute Deviation (MAD)	500
Skewness	0
Sum	2001000
Variance	333500
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2	1	0.1%
659	1	0.1%
685	1	0.1%
683	1	0.1%
681	1	0.1%
679	1	0.1%
677	1	0.1%
675	1	0.1%
673	1	0.1%
671	1	0.1%
Other values (1990)	1990	99.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%
6	1	0.1%
7	1	0.1%
8	1	0.1%
9	1	0.1%
10	1	0.1%

Value	Count	Frequency (%)
2000	1	0.1%
1999	1	0.1%
1998	1	0.1%
1997	1	0.1%
1996	1	0.1%
1995	1	0.1%
1994	1	0.1%
1993	1	0.1%
1992	1	0.1%
1991	1	0.1%

Blood_Pressure_Abnormality
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

0	1013
1	987

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	1

Common Values

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Most occurring characters

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1013	50.6%
1	987	49.4%

Level_of_Hemoglobin
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	757
Distinct (%)	37.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.710035

Minimum	8.1
Maximum	17.56
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	8.1
5-th percentile	8.58
Q1	10.1475
median	11.33
Q3	12.945
95-th percentile	16.01
Maximum	17.56
Range	9.46
Interquartile range (IQR)	2.7975

Descriptive statistics

Standard deviation	2.186700638
Coefficient of variation (CV)	0.1867373272
Kurtosis	-0.1842879759
Mean	11.710035
Median Absolute Deviation (MAD)	1.36
Skewness	0.6570660942
Sum	23420.07
Variance	4.781659679
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
12.07	11	0.5%
11.58	10	0.5%
11.54	9	0.4%
11.95	8	0.4%
10.89	8	0.4%
11.19	8	0.4%
10.98	8	0.4%
10.38	8	0.4%
10.55	8	0.4%
11.16	8	0.4%
Other values (747)	1914	95.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
8.1	2	0.1%
8.12	1	0.1%
8.13	4	0.2%
8.15	2	0.1%
8.16	2	0.1%
8.17	4	0.2%
8.18	3	0.1%
8.19	1	0.1%
8.2	2	0.1%
8.21	1	0.1%

Value	Count	Frequency (%)
17.56	1	0.1%
17.54	1	0.1%
17.53	1	0.1%
17.52	2	0.1%
17.51	1	0.1%
17.48	1	0.1%
17.45	1	0.1%
17.44	3	0.1%
17.39	1	0.1%
17.35	1	0.1%

Genetic_Pedigree_Coefficient
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	101
Distinct (%)	5.3%
Missing	92
Missing (%)	4.6%
Infinite	0
Infinite (%)	0.0%
Mean	0.4948165618

Minimum	0
Maximum	1
Zeros	17
Zeros (%)	0.9%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0.04
Q1	0.24
median	0.49
Q3	0.74
95-th percentile	0.9565
Maximum	1
Range	1
Interquartile range (IQR)	0.5

Descriptive statistics

Standard deviation	0.2917358818
Coefficient of variation (CV)	0.5895839071
Kurtosis	-1.17856276
Mean	0.4948165618
Median Absolute Deviation (MAD)	0.25
Skewness	0.01517745777
Sum	944.11
Variance	0.08510982475
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.86	32	1.6%
0.13	30	1.5%
0.63	28	1.4%
0.56	27	1.4%
0.17	27	1.4%
0.99	26	1.3%
0.25	25	1.2%
0.06	25	1.2%
0.46	25	1.2%
0.95	25	1.2%
Other values (91)	1638	81.9%
(Missing)	92	4.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	17	0.9%
0.01	23	1.1%
0.02	24	1.2%
0.03	17	0.9%
0.04	23	1.1%
0.05	15	0.8%
0.06	25	1.2%
0.07	11	0.5%
0.08	21	1.1%
0.09	21	1.1%

Value	Count	Frequency (%)
1	18	0.9%
0.99	26	1.3%
0.98	19	0.9%
0.97	18	0.9%
0.96	15	0.8%
0.95	25	1.2%
0.94	18	0.9%
0.93	13	0.7%
0.92	21	1.1%
0.91	11	0.5%

Age
Real number (ℝ_≥0)

Distinct	58
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	46.5585

Minimum	18
Maximum	75
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	18
5-th percentile	20
Q1	32
median	46
Q3	62
95-th percentile	73
Maximum	75
Range	57
Interquartile range (IQR)	30

Descriptive statistics

Standard deviation	17.10783203
Coefficient of variation (CV)	0.3674480928
Kurtosis	-1.248231524
Mean	46.5585
Median Absolute Deviation (MAD)	15
Skewness	0.02117832032
Sum	93117
Variance	292.6779167
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
18	46	2.3%
72	45	2.2%
21	43	2.1%
71	43	2.1%
25	41	2.1%
69	41	2.1%
53	41	2.1%
39	40	2.0%
29	40	2.0%
49	40	2.0%
Other values (48)	1580	79.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18	46	2.3%
19	27	1.4%
20	29	1.5%
21	43	2.1%
22	34	1.7%
23	27	1.4%
24	35	1.8%
25	41	2.1%
26	34	1.7%
27	37	1.8%

Value	Count	Frequency (%)
75	36	1.8%
74	39	1.9%
73	37	1.8%
72	45	2.2%
71	43	2.1%
70	32	1.6%
69	41	2.1%
68	38	1.9%
67	32	1.6%
66	34	1.7%

BMI
Real number (ℝ_≥0)

Distinct	41
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	30.0815

Minimum	10
Maximum	50
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	10
5-th percentile	11
Q1	20
median	30
Q3	40
95-th percentile	48
Maximum	50
Range	40
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	11.7612083
Coefficient of variation (CV)	0.3909781196
Kurtosis	-1.182620943
Mean	30.0815
Median Absolute Deviation (MAD)	10
Skewness	-0.0175554741
Sum	60163
Variance	138.3260208
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=41)

Value	Count	Frequency (%)
11	62	3.1%
38	62	3.1%
34	59	2.9%
26	59	2.9%
41	57	2.9%
21	57	2.9%
20	54	2.7%
40	53	2.6%
35	53	2.6%
15	52	2.6%
Other values (31)	1432	71.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	48	2.4%
11	62	3.1%
12	42	2.1%
13	38	1.9%
14	44	2.2%
15	52	2.6%
16	47	2.4%
17	39	1.9%
18	49	2.5%
19	45	2.2%

Value	Count	Frequency (%)
50	50	2.5%
49	46	2.3%
48	45	2.2%
47	49	2.5%
46	51	2.5%
45	45	2.2%
44	41	2.1%
43	52	2.6%
42	50	2.5%
41	57	2.9%

Sex
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

0	1008
1	992

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Most occurring characters

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1008	50.4%
1	992	49.6%

Pregnancy
Categorical

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	0.5%
Missing	1558
Missing (%)	77.9%
Memory size	15.8 KiB

0.0	243
1.0	199

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	1326
Distinct characters	3
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	243	12.2%
1.0	199	10.0%
(Missing)	1558	77.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	243	55.0%
1.0	199	45.0%

Most occurring characters

Value	Count	Frequency (%)
0	685	51.7%
.	442	33.3%
1	199	15.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	884	66.7%
Other Punctuation	442	33.3%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	685	77.5%
1	199	22.5%

Other Punctuation

Value	Count	Frequency (%)
.	442	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1326	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	685	51.7%
.	442	33.3%
1	199	15.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1326	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	685	51.7%
.	442	33.3%
1	199	15.0%

Smoking
Categorical

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

1	1019
0	981

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Most occurring characters

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1019	50.9%
0	981	49.0%

Physical_activity
Real number (ℝ_≥0)

Distinct	1951
Distinct (%)	97.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	25254.4245

Minimum	628
Maximum	49980
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	628
5-th percentile	3141.75
Q1	13605.75
median	25353
Q3	37382.25
95-th percentile	47170.2
Maximum	49980
Range	49352
Interquartile range (IQR)	23776.5

Descriptive statistics

Standard deviation	14015.43962
Coefficient of variation (CV)	0.5549696697
Kurtosis	-1.161726861
Mean	25254.4245
Median Absolute Deviation (MAD)	11893.5
Skewness	-0.01055936725
Sum	50508849
Variance	196432547.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
32903	2	0.1%
4591	2	0.1%
29513	2	0.1%
18629	2	0.1%
2971	2	0.1%
40046	2	0.1%
38769	2	0.1%
5673	2	0.1%
22664	2	0.1%
14479	2	0.1%
Other values (1941)	1980	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
628	1	0.1%
745	1	0.1%
768	2	0.1%
774	1	0.1%
784	1	0.1%
791	1	0.1%
799	1	0.1%
814	1	0.1%
829	1	0.1%
847	1	0.1%

Value	Count	Frequency (%)
49980	1	0.1%
49940	1	0.1%
49926	1	0.1%
49915	1	0.1%
49806	1	0.1%
49783	1	0.1%
49759	1	0.1%
49682	1	0.1%
49671	1	0.1%
49665	1	0.1%

salt_content_in_the_diet
Real number (ℝ_≥0)

Distinct	1945
Distinct (%)	97.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	24926.097

Minimum	22
Maximum	49976
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	22
5-th percentile	2462.1
Q1	13151.75
median	25046.5
Q3	36839.75
95-th percentile	47202.25
Maximum	49976
Range	49954
Interquartile range (IQR)	23688

Descriptive statistics

Standard deviation	14211.69259
Coefficient of variation (CV)	0.5701531446
Kurtosis	-1.154963837
Mean	24926.097
Median Absolute Deviation (MAD)	11813
Skewness	-0.02179784832
Sum	49852194
Variance	201972206.2
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
26353	2	0.1%
29324	2	0.1%
7545	2	0.1%
48995	2	0.1%
35221	2	0.1%
28517	2	0.1%
22942	2	0.1%
26474	2	0.1%
31366	2	0.1%
38265	2	0.1%
Other values (1935)	1980	99.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
22	1	0.1%
44	1	0.1%
58	1	0.1%
62	1	0.1%
66	1	0.1%
105	1	0.1%
144	1	0.1%
150	1	0.1%
154	1	0.1%
161	1	0.1%

Value	Count	Frequency (%)
49976	1	0.1%
49956	1	0.1%
49846	1	0.1%
49800	1	0.1%
49778	1	0.1%
49710	1	0.1%
49700	1	0.1%
49644	1	0.1%
49642	1	0.1%
49626	1	0.1%

alcohol_consumption_per_day
Real number (ℝ_≥0)

MISSING

Distinct	488
Distinct (%)	27.8%
Missing	242
Missing (%)	12.1%
Infinite	0
Infinite (%)	0.0%
Mean	251.0085324

Minimum	0
Maximum	499
Zeros	9
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	15.8 KiB

Quantile statistics

Minimum	0
5-th percentile	28.85
Q1	126.25
median	250
Q3	377.75
95-th percentile	473.15
Maximum	499
Range	499
Interquartile range (IQR)	251.5

Descriptive statistics

Standard deviation	143.6518844
Coefficient of variation (CV)	0.5722988101
Kurtosis	-1.217678643
Mean	251.0085324
Median Absolute Deviation (MAD)	126
Skewness	-0.008259128943
Sum	441273
Variance	20635.8639
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
253	11	0.5%
302	10	0.5%
144	10	0.5%
401	10	0.5%
347	9	0.4%
0	9	0.4%
485	9	0.4%
446	8	0.4%
206	8	0.4%
180	8	0.4%
Other values (478)	1666	83.3%
(Missing)	242	12.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	9	0.4%
1	3	0.1%
2	3	0.1%
3	5	0.2%
4	2	0.1%
5	4	0.2%
6	5	0.2%
8	4	0.2%
9	3	0.1%
11	4	0.2%

Value	Count	Frequency (%)
499	2	0.1%
497	1	0.1%
496	3	0.1%
495	5	0.2%
494	4	0.2%
493	1	0.1%
492	3	0.1%
491	4	0.2%
490	3	0.1%
488	4	0.2%

Level_of_Stress
Categorical

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

3	691
1	666
2	643

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	3
3rd row	2
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Most occurring characters

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
3	691	34.5%
1	666	33.3%
2	643	32.1%

Chronic_kidney_disease
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

0	1287
1	713

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	1
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Most occurring characters

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1287	64.3%
1	713	35.6%

Adrenal_and_thyroid_disorders
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	15.8 KiB

0	1404
1	596

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	2000
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Most occurring characters

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2000	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Most occurring scripts

Value	Count	Frequency (%)
Common	2000	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	1404	70.2%
1	596	29.8%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	Patient_Number	Blood_Pressure_Abnormality	Level_of_Hemoglobin	Genetic_Pedigree_Coefficient	Age	BMI	Sex	Pregnancy	Smoking	Physical_activity	salt_content_in_the_diet	alcohol_consumption_per_day	Level_of_Stress	Chronic_kidney_disease	Adrenal_and_thyroid_disorders
0	1	1	11.28	0.90	34	23	1	1.0	0	45961	48071	NaN	2	1	1
1	2	0	9.75	0.23	54	33	1	NaN	0	26106	25333	205.0	3	0	0
2	3	1	10.79	0.91	70	49	0	NaN	0	9995	29465	67.0	2	1	0
3	4	0	11.00	0.43	71	50	0	NaN	0	10635	7439	242.0	1	0	0
4	5	1	14.17	0.83	52	19	0	NaN	0	15619	49644	397.0	2	0	0
5	6	0	11.64	0.54	23	48	0	NaN	1	27042	7513	NaN	3	0	0
6	7	1	11.69	0.75	43	41	1	1.0	0	38369	32967	206.0	3	1	1
7	8	0	12.70	0.41	48	20	0	NaN	0	29781	26749	134.0	2	0	0
8	9	0	10.88	0.68	72	44	0	NaN	0	814	9607	99.0	3	0	0
9	10	1	14.56	0.61	40	44	0	NaN	0	1278	12715	95.0	2	0	0

Last rows

	Patient_Number	Blood_Pressure_Abnormality	Level_of_Hemoglobin	Genetic_Pedigree_Coefficient	Age	BMI	Sex	Pregnancy	Smoking	Physical_activity	salt_content_in_the_diet	alcohol_consumption_per_day	Level_of_Stress	Chronic_kidney_disease	Adrenal_and_thyroid_disorders
1990	1991	1	11.21	0.01	63	25	0	NaN	1	32903	4540	50.0	3	0	0
1991	1992	1	15.53	0.12	22	24	0	NaN	0	48325	16514	NaN	2	1	1
1992	1993	1	9.38	0.49	60	39	1	NaN	1	46591	29557	125.0	1	1	1
1993	1994	0	9.69	1.00	73	42	1	NaN	1	43344	36230	48.0	3	0	0
1994	1995	0	11.07	0.66	58	31	1	NaN	0	38603	22836	379.0	2	0	0
1995	1996	1	10.14	0.02	69	26	1	NaN	1	26118	47568	144.0	3	1	0
1996	1997	1	11.77	1.00	24	45	1	1.0	1	2572	8063	NaN	3	1	1
1997	1998	1	16.91	0.22	18	42	0	NaN	0	14933	24753	NaN	2	1	1
1998	1999	0	11.15	0.72	46	45	1	NaN	1	18157	15275	253.0	3	0	0
1999	2000	1	11.36	0.09	41	45	0	NaN	0	20729	30463	230.0	1	1	0

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Punctuation

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block